Using　a　linear　Kalman　filtering　approach　(LKFA),　the　finite-control-set　model　predictive　control　(FCS-　MPC)　proposes　for　DC-grid　voltage　estimation　control　in　direct　current　microgrid　systems　(DCMS).　The　proposed　control　algorithm　technique　addresses　real-time　measurements　needed　to　implement　the　FCS-MPC　by　adopting　the　LKFA　for　real-time　application.　The　state-space　model　is　used　to　produce　the　second　DCMS　predictive　model,　which　provides　access　to　a　sample　time　for　the　performance　of　an　efficient　algorithm.　The　dynamic　model　of　DCMS　is　transformed　into　a　stationary　linear　stochastic　discrete　time-invariant　system　to　standardize　the　state　estimation　design.　The　DC-grid　voltage　estimation　reference　is　computed　leveraging　LKFA　and　a　state　feedback　control　law　based　on　the　dynamic　algebraic　Riccati　equation　with　integral　action.　The　proposed　algorithm　has　been　verified　under　varying　load　demands.　Fast　computations,　DC-grid　voltage　estimation,　and　equally　estimated　power-sharing　between　DERs　have　all　been　realized.　©　2021　IEEE.